activity
20192022
most citedTemporal Consistency Learning of inter-frames for Video Super-Resolution

41 citations · 90 across the 6 of their papers we have counts for

collaborators

7 papers

cs.CV202241 cited

Temporal Consistency Learning of inter-frames for Video Super-Resolution

Meiqin Liu, Shuo Jin, Chao Yao +2

Video super-resolution (VSR) is a task that aims to reconstruct high-resolution (HR) frames from the low-resolution (LR) reference frame and multiple neighboring frames. The vital…

cs.CV202213 cited

Distortion-Tolerant Monocular Depth Estimation On Omnidirectional Images Using Dual-cubemap

Zhijie Shen, Chunyu Lin, Lang Nie +2

Estimating the depth of omnidirectional images is more challenging than that of normal field-of-view (NFoV) images because the varying distortion can significantly twist an object'…

cs.CV20215 cited

Depth-Aware Multi-Grid Deep Homography Estimation with Contextual Correlation

Lang Nie, Chunyu Lin, Kang Liao +2

Homography estimation is an important task in computer vision applications, such as image stitching, video stabilization, and camera calibration. Traditional homography estimation…

cs.CV20217 cited

Towards Fast and Accurate Real-World Depth Super-Resolution: Benchmark Dataset and Baseline

Lingzhi He, Hongguang Zhu, Feng Li +6

Depth maps obtained by commercial depth sensors are always in low-resolution, making it difficult to be used in various computer vision tasks. Thus, depth map super-resolution (SR)…

cs.CV202023 cited

Learning Edge-Preserved Image Stitching from Large-Baseline Deep Homography

Lang Nie, Chunyu Lin, Kang Liao +1

Image stitching is a classical and crucial technique in computer vision, which aims to generate the image with a wide field of view. The traditional methods heavily depend on the f…

cs.CV20201 cited

Pseudo-LiDAR Point Cloud Interpolation Based on 3D Motion Representation and Spatial Supervision

Haojie Liu, Kang Liao, Chunyu Lin +2

Pseudo-LiDAR point cloud interpolation is a novel and challenging task in the field of autonomous driving, which aims to address the frequency mismatching problem between camera an…